Open AccessOptimized stable gait planning of biped robot using multi-objective evolutionary JAYA algorithm
Author(s) -
Huan Tran Thien,
Cao Van Kien,
Hồ Phạm Huy Ánh
Publication year - 2020
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.1177/1729881420976344
Subject(s) - biped robot , computer science , control theory (sociology) , gait , kinematics , inverse kinematics , stability (learning theory) , multi objective optimization , digital pattern generator , robot , generator (circuit theory) , simulation , algorithm , control (management) , artificial intelligence , telecommunications , chip , power (physics) , physics , classical mechanics , quantum mechanics , machine learning , physiology , biology
This article proposes a new stable biped walking pattern generator with preset step-length value, optimized by multi-objective JAYA algorithm. The biped robot is modeled as a kinetic chain of 11 links connected by 10 joints. The inverse kinematics of the biped is applied to derive the specified biped hip and feet positions. The two objectives related to the biped walking stability and the biped to follow the preset step-length magnitude have been fully investigated and Pareto optimal front of solutions has been acquired. To demonstrate the effectiveness and superiority of proposed multi-objective JAYA, the results are compared to those of MO-PSO and MO-NSGA-2 optimization approaches. The simulation and experiment results investigated over the real small-scaled biped HUBOT-4 assert that the multi-objective JAYA technique ensures an outperforming effective and stable gait planning and walking for biped with accurate preset step-length value.
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